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The Exponentiated Normal Regression Model with Application

Eman Madkour et al.

Journal of Statistical Theory and Applications2026https://doi.org/10.1007/s44199-026-00163-0article
ABDC C
Weight
0.50

What the paper says

Abstract This paper introduces a novel regression model based on the Exponentiated Normal (Exp-N) distribution and compares its performance with traditional Normal regression. Using the maximum likelihood method, parameters for both the regression structure and the underlying distributions were estimated. The Exp-N regression model was thoroughly investigated, with several new statistical properties derived and validated. Applied to a real-world dataset of testosterone hormone levels, the model demonstrated superior goodness-of-fit over the conventional Normal regression, offering a more flexible and accurate framework for data analysis in medical and biological research.

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https://doi.org/https://doi.org/10.1007/s44199-026-00163-0

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@article{eman2026,
  title        = {{The Exponentiated Normal Regression Model with Application}},
  author       = {Eman Madkour et al.},
  journal      = {Journal of Statistical Theory and Applications},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1007/s44199-026-00163-0},
}

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The Exponentiated Normal Regression Model with Application

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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